Founding Cloud Infrastructure Engineer - AIOps

Job Description :

YMinds.AI is an Artificial Intelligence company building next-generation AI solutions across Recruitment Technology, Enterprise AI, Agentic AI, Generative AI, and Intelligent Automation. Our mission is to develop scalable, AI-first products that help businesses automate complex workflows and accelerate digital transformation.

We're looking for a Founding AWS Cloud Engineer to architect, build, and scale the cloud infrastructure powering our AI-native platforms.

This is a true Zero-to-One (0-1) engineering opportunity. There are no legacy systems to inherit or existing architectures to maintain. You will define the cloud architecture, security standards, DevSecOps practices, and infrastructure strategy that will serve as the foundation of our products for years to come.

You will work closely with AI Engineers, Backend Engineers, Product Teams, and Leadership to build secure, scalable, reliable, and production-ready cloud infrastructure for modern AI applications.

Top 6 Must-Have Skills (Mandatory) :

1. Zero-to-One AWS Infrastructure Architecture (Mandatory) :

Demonstrated experience designing and building production-grade AWS cloud infrastructure from scratch. Candidates must have independently owned architecture decisions, infrastructure design, and platform scalability in a startup or greenfield environment.

2. Deep AWS Expertise :

Strong hands-on experience with AWS services including : EC2, ECS, VPC, IAM, S3, RDS, Route 53, CloudFront, CloudWatch, Elastic Load Balancers, Auto Scaling, NAT Gateway, and Security Groups.

3. Infrastructure as Code (Terraform) :

Extensive experience building and managing infrastructure using Terraform, with modular architecture, automation, version control, and environment management.

4. DevSecOps & CI/CD Automation :

Hands-on expertise with Docker, CI/CD pipelines, infrastructure security, secrets management, vulnerability management, deployment automation, and cloud security best practices.

5. AI Infrastructure & Distributed Systems :

Experience supporting AI/LLM applications, RAG architectures, vector databases, GPU infrastructure, event-driven systems, and distributed cloud-native applications.

6. Production Reliability & Cloud Operations :

Strong knowledge of Linux, networking, monitoring, logging, observability, incident management, disaster recovery, high availability, scalability, and cloud cost optimization.

Mandatory Requirement :

Founding / Zero-to-One Experience (Non-Negotiable) :

This role is intended for an engineer who has built cloud platforms from the ground up, not someone whose experience is primarily maintaining existing infrastructure. Candidates must have demonstrated experience designing, implementing, securing, and scaling production AWS infrastructure from Zero-to-One, making architectural decisions independently and establishing engineering best practices. Applicants whose experience is primarily focused on operations, production support, or maintaining mature cloud environments without ownership of foundational architecture are unlikely to be a fit.

Key Responsibilities :

- Design and build secure, scalable, and highly available AWS cloud infrastructure from scratch.

- Architect production-grade cloud platforms capable of supporting AI-native applications.

- Build and maintain Infrastructure as Code using Terraform.

- Design and implement secure CI/CD pipelines for automated deployments.

- Deploy and manage containerized applications using Docker and Amazon ECS (or Kubernetes where applicable).

- Design secure cloud networking including VPCs, Subnets, Route Tables, NAT Gateways, Security Groups, Internet Gateways, VPNs, and Load Balancers.

- Implement IAM policies, encryption, secrets management, and infrastructure security best practices.

- Build infrastructure supporting AI workloads including LLM inference, Retrieval-Augmented Generation (RAG), vector databases, and AI agents.

- Collaborate closely with AI Engineers to optimize cloud environments for model training and inference.

- Design monitoring, logging, tracing, alerting, and observability solutions.

- Build automated backup, disaster recovery, and business continuity strategies.

- Optimize infrastructure for performance, scalability, reliability, and cloud cost efficiency.

- Own production reliability, incident management, root cause analysis, and continuous improvement.

- Drive infrastructure automation and platform engineering best practices across the organization.

- Evaluate and introduce new cloud technologies that improve engineering productivity and platform capabilities.

Required Qualifications :

- Bachelor's or Master's degree in Computer Science, Information Technology, or a related field.

- 6-12+ years of hands-on AWS Cloud Engineering experience.

- Proven experience building cloud platforms from Zero-to-One.

- Strong experience with AWS production environments.

- Deep understanding of cloud networking and security.

- Extensive Terraform experience.

- Strong Linux administration skills.

- Experience with Docker and containerized workloads.

- Experience building secure CI/CD pipelines.

- Strong scripting skills using Bash, Python, or similar languages.

- Experience designing highly available distributed systems.

- Strong debugging and production troubleshooting skills.

- Excellent communication and technical decision-making abilities.

Preferred Technical Skills :

1. Cloud & Containers : Amazon ECS, Amazon EKS, Kubernetes, Docker, AWS Lambda, EventBridge, Step Functions, API Gateway.

2. Messaging & Data : Kafka, Amazon SQS, Amazon SNS, Redis, RabbitMQ, PostgreSQL, MongoDB.

3. AI Infrastructure : LangChain, LangGraph, LlamaIndex, OpenAI APIs, Anthropic APIs, Ollama, vLLM, NVIDIA GPU Infrastructure, CUDA, Triton Inference Server.

4. Vector Databases : Pinecone, Weaviate, Qdrant, pgVector, Milvus.

5. Observability : Prometheus, Grafana, ELK Stack, CloudWatch, OpenTelemetry.

6. Security : AWS Secrets Manager, AWS KMS, AWS WAF, AWS Shield, IAM Identity Center.

What We're Looking For :

- Loves building systems from the ground up.

- Thinks like an architect rather than an operator.

- Takes complete ownership of technical decisions.

- Enjoys solving complex infrastructure problems.

- Builds scalable systems with long-term thinking.

- Is passionate about automation and Infrastructure as Code.

- Thrives in startup environments with high ownership and minimal bureaucracy.

- Has a strong bias for action and execution.

- Enjoys working alongside AI Engineers and Product teams to bring innovative ideas into production.

- Continuously explores emerging cloud technologies and AI infrastructure.

(ref:hirist.tech)